Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to those gotten from other popular methods inthis field, such as Zero Crossing Rate (ZCR), Amplitude Descriptor (AD), Short Time Energy (STE), and Volume (Vo). The test results indicated, that the attained averageaccuracy of classification is improved up to94.9232% for training set and 95.8666%for testing set.The classification performance of these two extracted featuresets is studied individually, and then they used together as one feature set. Theiroverall performance is investigated, the test results showed that the proposed methods give high classification rates for the audio.
Generally the a.c. conductivity shows a power law in frequency s () where the exponent s ≤ 1. As the frequency goes to zero the conductivity become frequency independent. The a.c. conductivity was studied for the Ge1-xSex thin films to see how the selenium contents affect the permittivity and the permeability for the Ge1-x Sex. The thin films prepared by thermal evaporation at room temperature and under vacuum (~2 x10-5toor) using Edward coating unit model 306A. From the relation between ln conductivity and ln w, the effect of selenium contents in Ge1-x Sex thin films on the exponent value, the relaxation time and the maximum barrier height. An algebric fitting method for circles and circular arcs was used to find the permit
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Abstract:
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In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between ev
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In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water
... Show MoreNS-2 is a tool to simulate networks and events that occur per packet sequentially based on time and are widely used in the research field. NS-2 comes with NAM (Network Animator) that produces a visual representation it also supports several simulation protocols. The network can be tested end-to-end. This test includes data transmission, delay, jitter, packet-loss ratio and throughput. The Performance Analysis simulates a virtual network and tests for transport layer protocols at the same time with variable data and analyzes simulation results based on the network simulator NS-2.
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Five sites were chosen to the north of Babil Governorate in order to identify the limnological features and the impact of the Hindiya Dam during 2019. Site2 was located near the dam to reflect the ecological features of this site, whereas other sites, S1 was located at the upstream of the dam as a control site. Moreover, the two other sites S3 and S4 were located down the dam. The results of the study showed a close correlation between air and water temperature at all sites. Also there were significant differences in average of thirteen out of eighteen water parameters.Water temperature, total alkalinity, bicarbonate, DO, POS, TH and Mg+2 ions decreased from 22.76˚C, 203.33 mg/L,
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1.Chapter I (systematic framework) which includes: the research problem and the importance of the research, the need for it, the goals of the research, the temporal &spatial boundaries, determine the terms and defined procedurally.2.Chapter II - the theoretical framework: It consists of three sections are:•The first topic:- the concept of references and experimentation in the theater. •The second topic:- the director of academic and experimentation in Iraq. Two paragraphs in this section came after the introduction, in first paragraph to talk about the Iraqi theater academic and experimentation, and in the second paragraph the researcher spoke about the academic director of the Iraqi and experimentation. 3.Chapter III - Actions -
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